Imaging for Scapholunate Ligament Injuries: Techniques, Challenges, and Innovations

Scapholunate (SL) ligament injuries are a common cause of wrist pain and instability but can be diagnostically challenging. Standard radiographs, ultrasound, computed tomography, and magnetic resonance imaging have been used for many years to assist in the diagnosis of these injuries, and all of them have benefits and limitations. Advanced dynamic modalities, such as real-time magnetic resonance imaging and four-dimensional computed tomography, can distinguish functional from static injuries but are not widely available. The emergence of artificial intelligence applications is promising to improve diagnostic accuracy in automated SL gap detection and kinematic analysis. As each imaging modality presents strengths and trade-offs in terms of invasiveness, resolution, and dynamic assessment, combining imaging with thorough clinical examination remains essential. This current concepts review summarizes modern imaging techniques for SL ligament injuries and highlights emerging innovations.

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Publication Details

Journal
The Journal Of Hand Surgery
Published
2026-02-01
DOI
https://doi.org/10.1016/j.jhsa.2025.11.021
Primary Topic
Orthopedic Surgery and Rehabilitation
Type
article
Field-Weighted Citation Impact
0.00
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article

Imaging for Scapholunate Ligament Injuries: Techniques, Challenges, and Innovations

Jonathan Persitz, Kevin J. Zuo, Adham Elsherbini, Laura Saenz
The Journal Of Hand Surgery
Orthopedic Surgery and Rehabilitation
article

Imaging for Scapholunate Ligament Injuries: Techniques, Challenges, and Innovations

Jonathan Persitz, Kevin J. Zuo, Adham Elsherbini, Laura Saenz
article en

Abstract

Scapholunate (SL) ligament injuries are a common cause of wrist pain and instability but can be diagnostically challenging. Standard radiographs, ultrasound, computed tomography, and magnetic resonance imaging have been used for many years to assist in the diagnosis of these injuries, and all of them have benefits and limitations. Advanced dynamic modalities, such as real-time magnetic resonance imaging and four-dimensional computed tomography, can distinguish functional from static injuries but are not widely available. The emergence of artificial intelligence applications is promising to improve diagnostic accuracy in automated SL gap detection and kinematic analysis. As each imaging modality presents strengths and trade-offs in terms of invasiveness, resolution, and dynamic assessment, combining imaging with thorough clinical examination remains essential. This current concepts review summarizes modern imaging techniques for SL ligament injuries and highlights emerging innovations.

The Journal Of Hand Surgery
University Health Network (CA), University of Toronto (CA), Toronto Western Hospital (CA)
Openalex Percentile: Top 67%
Orthopedic Surgery and Rehabilitation
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